Forecasting the evolution of bacteria in a specialization context : a functional approach combining modelling, in vitro experiments and genomic analysis

Abstract: Is evolution predictable? While the usual response is an almost unanimous No, a growing corpus of knowledge suggests that it is time to revisit this answer. Even though mutations are still assumed to be random, the detection of genetic patterns underlying evolutionary events opens the door on potential strategies to forecast the evolutionary trajectories followed by organisms when they adapt to changing constraints. When organisms undergo functional specialization to adapt to given environmental cues, the possible evolutionary paths they can take are restrained and should thus be more easily predictable. In this context of reductive evolution through specialization, the objectives of this thesis are to understand better the interaction between environmental constraints, metabolism, genetic evolution and functional adaptations, and in a second time to predict, for given environmental constraints, the evolutionary trajectories which will be followed by organisms to adapt to these constraints. A first approach investigates how changes entailed in metabolisms and functions by a change in environmental constraints could be forecast and tested. Based on a metabolic-centered view, we combined modelling and experimental work to encompass the evolution of specialization at the genetic, metabolic and functional levels. We show that evolution trajectories can partially be predicted according to specific environmental conditions, but that these predictions are limited due to the intricacy of the genetic expression network. A second approach focuses on the importance of biotic interactions as being determinants of evolutionary trajectories, and how by modelling a beneficial rise of dependency on a common good, we could predict the dynamics of a population undergoing such evolutionary events. This interdisciplinary work explores evolutionary determinants and trajectories followed by organism during specialization. It also demonstrates potential for predictions, notably through a metabolic perception of the systems.